The FilterBubbler project is an easy-to-use page classifier and explorer that gives users measurements of the statistical similarities of the current page to known text corpora, or “bubbles”. It uses the cross-platform WebExtensions add-on interface and is adaptable for use in social games, productivity tools, recommendation tools, and self-discipline/quantified self tasks. Users can get a bubble summary or explore in more detail.

Page classifications are initially user generated. A user can mark arbitrary URLs as either an example or a counter-example of a given filter bubble. These classification corpora can then be matched by pluggable text classifiers that can report data back to the user using a common UI. Configurations of corpus set feeds and algorithms will be published to configurable “bubble servers” that users can load configurations from. Bubble servers will then register themselves with a central server to make it easier for users to discover them.

FilterBubbler shows how a resource-intensive application can run in-browser to help developers advocate for “web technologies everywhere” over native apps and server-side code.

Learn about the WebExtensions technology that InfoBubbles uses to control the browser, the WordPress plug-in for sharing corpus information and the JavaScript text classification framework that is all based on.

This project will be designed to work with Google Chrome as well as Firefox, although initial development will be done in Firefox. All text handling will be client-side, with no text sent to the server, for several reasons.

User privacy, to allow classification of “sensitive” pages

Copyright issues, so that we can match against copyrighted text

Learning: gather more data about what is possible to do in the browser

Performance/budget, to require fewer server-side resources

FilterBubbler shows how a resource-intensive application can run in-browser to help developers advocate for “web technologies everywhere” over native apps and server-side code.